Abstract: TRD 3. Nuclear magnetic resonance spectroscopy (NMR) is a powerful analytical instrument with numerous applications in biomedicine. Some examples of high-impact investigation are studies using metabolite profiles as markers of health status, evaluation of small molecules for biological activity as a drug, and discovery of new metabolic compounds. NMR offers detailed information, but the interpretation of data involves a multistep process that often involves using data from other analytical instruments. The use of a range of sophisticated mathematical and computational methods is required, and this is often a major bottleneck. The aim of this TRD is to deliver enhanced functionality for robust and reliable statistical framework, based on Bayesian principles. This project will advance the state of NMR data analytics and simplifies the future development of advanced NMR applications. Central components of this TRD include a Bayesian inference engine, tools for validation of experimental models and results, a set of programming interfaces, and a library of templates for facilitating the identification of metabolite and small molecule signatures in biological mixtures. The implementation of this TRD will benefit from key advantages offered by the NMRbox platform. By facilitating the deployment, utilization, interoperation, and persistence of this advanced technology, the proposed TRD will advance the application of NMR for a wide range of challenging applications in biomedicine and helps ensure the reproducibility bio-NMR studies.